RESUMEN
The transplantation of neonatal microglia suppresses neuroinflammation caused by traumatic brain injury (TBI). This research aimed to explore the optimal time point of neonatal microglia transplantation for the best effect on the improvement of long-term cognitive function and inflammatory response in mouse models. qPCR and immunoblotting showed that the level of Iba1 gradually increased to the highest on day 7 and then gradually declined in TBI mice. Furthermore, it was observed that the level of CD86 and TNF-α increased to the highest after 7 days and subsequently was maintained until day 21, whereas the level of CD206 and IL-10 increased to the highest after 24 h and subsequently decreased until day 21 by qPCR and enzyme-linked immunosorbent assay. Afterward, it was shown that the neonatal microglia transplantation within 1 h significantly attenuated anxiety-like behavior and improved cognitive impairments in TBI mice. Mechanism exploration showed that the neonatal microglia could significantly decrease the level of cleaved caspase-3, M1/M2 polarization, and inflammatory cytokine (TNF-α) while increasing the level of anti-inflammatory factor IL-10 in TBI mice after transplantation within 1 h. Here, our findings demonstrated that neonatal microglia transplantation within 1 h significantly attenuated anxiety-like behavior and cognitive impairments caused by TBI.NEW & NOTEWORTHY The study demonstrated that neonatal microglia transplantation within 1 h significantly inhibited the pathogenesis of traumatic brain injury (TBI) in mouse models through inhibition of M1 polarization and promotion of M2 polarization.
Asunto(s)
Lesiones Traumáticas del Encéfalo , Microglía , Ratones , Animales , Interleucina-10/farmacología , Factor de Necrosis Tumoral alfa/farmacología , Antiinflamatorios/farmacología , Ratones Endogámicos C57BLRESUMEN
Gliomas are malignant tumors of the central nervous system; current treatment methods have low efficacy. Twisted gastrulation BMP signaling modulator 1 (TWSG1) has been shown to play a role in gliomas but it is not known whether TWSG1 participates in glioma pathogenesis and macrophage immune regulation. This study identified a total of 24 differentially expressed genes with survival differences in gliomas using bioinformatics analysis. Among them, TWSG1 exhibited the strongest correlation with gliomas and was positively correlated with macrophage enrichment. The results showed that TWSG1 was highly expressed in various glioma cell lines, with the highest expression observed in the A172 cell line. Silencing TWSG1 significantly decreased the viability, migration, and invasion of A172 cells in vitro and tumor growth in a mouse xenograft model in vivo. It also reduced the expression of the matrix metalloproteinases MMP2 and MMP9 both in vivo and in vitro. Silencing TWSG1 significantly reduced the expression of M2 macrophage makers and upregulated the expression of M1 macrophage markers in A172 cells and tumor tissues. These data suggest that interference with TWSG1 suppressed the progression of A172 glioma cells and regulated immune infiltration.
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Objective: Numerous studies have posited the involvement of serum uric acid (SUA) in the pathogenesis and progression of various cardiovascular diseases, particularly aortic aneurysms. However, the casual effect of SUA level on intracranial aneurysms (IAs) was rarely studied. Consequently, we aimed to explore the causal association between SUA and IAs using Mendelian randomization (MR) analysis. Methods: We conducted a two-sample MR analysis with SUA as the exposure variable and IAs as the outcome variable. Genome-wide association study (GWAS) datasets for SUA were acquired from the Open GWAS catalog, including 389,404 European and 129,405 East Asian individuals. The dataset for IAs was sourced from a meta-analysis of GWASs comprising 317,636 individuals across different ancestral populations (European: 7495 cases and 71,934 controls; East Asian: 3259 cases and 234,948 controls). The MR analyses were performed according to populations (European and East Asian) and IAs status [unruptured IAs (uIAs) or aneurysmal subarachnoid hemorrhage (aSAH)], respectively. The inverse variance weighted (IVW) method was employed as primary analysis to discern causal estimates. Results: Our findings revealed that an elevated genetically predicted SUA level (mg/dL) correlated with an increased risk of IAs among the European population (OR = 1.29 [95%CI:1.05-1.57], P = 0.013) and East Asian population (OR = 1.56 [95%CI: 1.27-1.92], P < 0.001). Among European individuals, subgroup analysis indicated a persistent causal association of SUA with uIAs (OR = 1.50 [95%CI: 1.08-2.08], P = 0.015) and aSAH (OR = 1.26 [95%CI: 1.00-1.60], P = 0.049). However, subgroup analysis in East Asian populations was not conducted due to the lack of separate data on uIAs and aSAH. Conclusions: Our MR analysis demonstrated a causal relationship between elevated SUA levels and an amplified risk of IAs. Further rigorous investigations are imperative to provide evidence and elucidate the underlying mechanisms.
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Background: Blood pressure (BP) is a key factor for the clinical outcomes of acute ischemic stroke (AIS) receiving endovascular thrombectomy (EVT). However, the effect of the circadian pattern of BP on functional outcome is unclear. Methods: This multicenter, retrospective, observational study was conducted from 2016 to 2023 at three hospitals in China (ChiCTR2300077202). A total of 407 patients who underwent endovascular thrombectomy (EVT) and continuous 24-h BP monitoring were included. Two hundred forty-one cases from Beijing Hospital were allocated to the development group, while 166 cases from Peking University Shenzhen Hospital and Hainan General Hospital were used for external validation. Postoperative systolic BP (SBP) included daytime SBP, nighttime SBP, and 24-h average SBP. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), Boruta were used to screen for potential features associated with functional dependence defined as 3-month modified Rankin scale (mRS) score ≥ 3. Nine algorithms were applied for model construction and evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Results: Three hundred twenty-eight of 407 (80.6%) patients achieved successful recanalization and 182 patients (44.7%) were functional independent. NIHSS at onset, modified cerebral infarction thrombolysis grade, atrial fibrillation, coronary atherosclerotic heart disease, hypertension were identified as prognostic factors by the intersection of three algorithms to construct the baseline model. Compared to daytime SBP and 24-h SBP models, the AUC of baseline + nighttime SBP showed the highest AUC in all algorithms. The XGboost model performed the best among all the algorithms. ROC results showed an AUC of 0.841 in the development set and an AUC of 0.752 in the validation set for the baseline plus nighttime SBP model, with a brier score of 0.198. Conclusion: This study firstly explored the association between circadian BP patterns with functional outcome for AIS. Nighttime SBP may provide more clinical information regarding the prognosis of patients with AIS after EVT.
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This study aimed to evaluate the potential of cluster of differentiation 86 (CD86) as a biomarker in high-grade glioma (HGG). The TCGA and TCIA databases were used to obtain the CD86 expression value, clinical data, and MRI images of HGG patients. Prognostic values were assessed by the Kaplan-Meier method, Receiver operating characteristic curve (ROC), Cox regression, logistic regression, and nomogram analyses. CD86-associated pathways were also explored. We found that CD86 was significantly upregulated in HGG compared with the normal group. Survival analysis showed a significant association between CD86 high expression and shorter overall survival time. Its independent prognostic value was also confirmed. These results suggested the possibility of CD86 as a biomarker in HGG. We also innovatively established 2 radiomics models with Support Vector Machine (SVM) and Logistic regression (LR) algorithms to predict the CD86 expression. The 2 models containing 5 optimal features by SVM and LR methods showed similar favorable performance in predicting CD86 expression in the training set, and their performance were also confirmed in validation set. These results indicated the successful construction of a radiomics model for non-invasively predicting biomarker in HGG. Finally, pathway analysis indicated that CD86 might be involved in the natural killer cell-mediated cytotoxicity in HGG progression.